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Air Base Station-Assisted Communications for Maritime Internet of Things
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Air Base Station-Assisted Communications for Maritime Internet of Things

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: closed (5 February 2024) | Viewed by 4914

Special Issue Editors

Dr. Dawei Wang

E-Mail Website
Guest Editor
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Interests: UAV communications; physical-layer security; resource allocation
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ruonan Zhang

E-Mail Website
Guest Editor
School of Electronics and Information, Northwestern Polytechnical University, Xi'an 710072, China
Interests: wireless channel measurement and modeling; architecture and protocol design of wireless networks; satellite communications
Special Issues, Collections and Topics in MDPI journals
Dr. Yixin He

E-Mail Website
Guest Editor
College of Information Science and Engineering, Jiaxing University, Jiaxing, China
Interests: VANETs; resource allocation; UAV communications

Special Issue Information

Dear Colleagues,

In recent years, a growing number of physical maritime objects have been connected to the Internet at an unprecedented rate, calcifying the idea of the maritime Internet of Things (IoT). In many paradigms of maritime IoT applications, air base stations (ABSs), e.g., unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and low-altitude platforms (LAPs), for maritime IoTs have attracted significant attention and have experienced rapid development. Under these circumstances, the seamless integration of ABSs and maritime networks is critical to fully unlock the potential benefits of emerging maritime IoTs use cases, such as smart ports, autonomous navigation, and ocean monitoring systems.

This Special Issue will focus on the enabling technologies, challenges, and future research directions in the ABS-aided maritime IoTs in order to satisfy the increasing demands for maritime remote sensing services. The following topics will be considered:

  • Positioning and navigation;
  • Network architectures and protocols for maritime IoTs;
  • Access and backhaul management strategies for maritime IoTs;
  • Experimental demos, prototyping, and field-trials for maritime IoTs;
  • Energy model and energy supplying methods of maritime IoTs;
  • Physical-layer security of maritime IoTs;
  • Channel measurements and modeling for ABS-to-ship links;
  • Performance analysis of ABS-aided maritime IoTs;
  • Mobile edge computing (MEC) for ABS-aided maritime IoTs;
  • Spectrum management and multiple access schemes for ABS-aided maritime IoTs;
  • Machine learning and AI for enabling fully autonomous ABS-aided maritime IoTs;
  • Hybrid satellite–ABS terrestrial maritime IoTs;
  • Intelligent vessel traffic services.

Dr. Dawei Wang
Prof. Dr. Ruonan Zhang
Dr. Yixin He
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

21 pages, 1509 KiB  
Article
UAV Relay Energy Consumption Minimization in an MEC-Assisted Marine Data Collection System
by Woping Xu and Li Gu
J. Mar. Sci. Eng. 2023, 11(12), 2333; https://doi.org/10.3390/jmse11122333 - 10 Dec 2023
Viewed by 983
Abstract
Recently, unmanned aerial vehicle (UAV)-assisted maritime communication systems have drawn considerable attention due to their potential for broadband maritime communication applications. However, their limited energy resources remains a critical issue in providing long-term data transmission support for maritime applications. In this study, an [...] Read more.
Recently, unmanned aerial vehicle (UAV)-assisted maritime communication systems have drawn considerable attention due to their potential for broadband maritime communication applications. However, their limited energy resources remains a critical issue in providing long-term data transmission support for maritime applications. In this study, an integrated sea–air–terrestrial communication system was constructed for marine data collection, where several unmanned surface vessels (USVs) are deployed to collect marine data from underwater sensors (UWSs), and a UAV hovers above these USVs as a relay node, transmitting marine data from USVs to an onshore base station (BS). To prolong the lifetime of the UAV relay, mobile edge computing technology is applied in USVs for partial data computing, which reduces the to-be-relayed data volume from UAVs to USVs to onshore BS as well as the relay energy consumption of UAV. A parallel data computing and transmission scheme was developed for simultaneous local data computing and relaying in the proposed system. Accordingly, a UAV energy consumption minimization problem was formulated with constraints on the USV’s computational ability, the USV’s transmission power budget, the UAV transmission power budget, and the maximum system latency. To effectively solve this nonconvex optimal problem, an energy optimal partial data computing and relaying strategy was constructed by successively optimizing the data partial computational offloading ratio, USV transmit power allocation, and UAV transmit power. Numerical simulations were used to verify the effectiveness of the proposed strategy. Full article
(This article belongs to the Special Issue Air Base Station-Assisted Communications for Maritime Internet of Things)
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15 pages, 4439 KiB  
Article
A Sea Fog Image Defogging Method Based on the Improved Convex Optimization Model
by He Huang, Zhanyi Li, Mingbo Niu, Md Sipon Miah, Tao Gao and Huifeng Wang
J. Mar. Sci. Eng. 2023, 11(9), 1775; https://doi.org/10.3390/jmse11091775 - 11 Sep 2023
Cited by 1 | Viewed by 962
Abstract
Due to the high fog concentration in sea fog images, serious loss of image details is an existing problem, which reduces the reliability of aerial visual-based sensing platforms such as unmanned aerial vehicles. Moreover, the reflection of water surface and spray can easily [...] Read more.
Due to the high fog concentration in sea fog images, serious loss of image details is an existing problem, which reduces the reliability of aerial visual-based sensing platforms such as unmanned aerial vehicles. Moreover, the reflection of water surface and spray can easily lead to overexposure of images, and the assumed prior conditions contained in the traditional fog removal method are not completely valid, which affects the restoration effectiveness. In this paper, we propose a sea fog removal method based on the improved convex optimization model, and realize the restoration of images by using fewer prior conditions than that in traditional methods. Compared with dark channel methods, the solution of atmospheric light estimation is simplified, and the value channel in hue–saturation–value space is used for fusion atmospheric light map estimation. We construct the atmospheric scattering model as an improved convex optimization model so that the relationship between the transmittance and a clear image is deduced without any prior conditions. In addition, an improved split-Bregman iterative method is designed to obtain the transmittance and a clear image. Our experiments demonstrate that the proposed method can effectively defog sea fog images. Compared with similar methods in the literature, our proposed method can actively extract image details more effectively, enrich image color and restore image maritime targets more clearly. At the same time, objective metric indicators such as information entropy, average gradient, and the fog-aware density evaluator are significantly improved. Full article
(This article belongs to the Special Issue Air Base Station-Assisted Communications for Maritime Internet of Things)
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30 pages, 9678 KiB  
Article
A Novel Region-Construction Method for Multi-USV Cooperative Target Allocation in Air–Ocean Integrated Environments
by Zeyu Zhou, Mingyang Li and Yun Hao
J. Mar. Sci. Eng. 2023, 11(7), 1369; https://doi.org/10.3390/jmse11071369 - 05 Jul 2023
Cited by 4 | Viewed by 976
Abstract
The effective defense of sparsely populated border islands, surrounded by a multifaceted sea, against enemy infiltration poses a crucial problem in national defense. One possible solution is to deploy multiple unmanned surface vessels (USVs) to form an intelligent patrol and defense system. With [...] Read more.
The effective defense of sparsely populated border islands, surrounded by a multifaceted sea, against enemy infiltration poses a crucial problem in national defense. One possible solution is to deploy multiple unmanned surface vessels (USVs) to form an intelligent patrol and defense system. With the designated or daily patrols of USVs, we need to allocate target positions in real time to ensure their continuous operation. Currently, the state-of-art methods contain two major problems of target deadlock and local optimization, which limit the efficiency of reaching the target. To this end, we proposed a novel Region-Construction (RECO) method aimed at high-efficiency target allocation. Firstly, a dynamic calculation approach in K value for unsupervised clustering and time factor’s lead-in for Market-Based Mechanism (MBM) method was created to resolve potential target deadlock among USVs. Secondly, we proposed a novel construction strategy in a non-complete graph (NCG) consisting of neighborhood connection and pheromone extension to provide enough feasible nodes for solution searching. Finally, we introduced adjustment of search range and edge weights, and activated node interaction in traditional Ant Colony Optimization (ACO) algorithm in NCG to obtain the optimal combination of each USV’s target allocations. We established a simulation platform with an airborne managing base station and several USVs. The experimental results demonstrated that when the number of USVs was four, the average time for all USVs to reach the target in the RECO method reduced by 10.9% and 7.7% compared to the MBM and ACO methods, respectively. This reduction was 25% and 11.6% for 6 USVs, 25.7% and 21.8% for 8 USVs, 20% and 19% for 10 USVs. It reflects that the proposed RECO allocation method has shown improvements in terms of successfully-assigned USVs’ quantity and operational efficiency, compared to the state-of-art MBM and ACO algorithms. Full article
(This article belongs to the Special Issue Air Base Station-Assisted Communications for Maritime Internet of Things)
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14 pages, 601 KiB  
Article
Secure Rate-Splitting Multiple Access for Maritime Cognitive Radio Network: Power Allocation and UAV’s Location Optimization
by Lingtong Min, Jiawei Li, Yixin He and Weiguang Wang
J. Mar. Sci. Eng. 2023, 11(5), 1012; https://doi.org/10.3390/jmse11051012 - 09 May 2023
Viewed by 1250
Abstract
This paper investigates the secure rate-splitting multiple access (RSMA) cooperation for the maritime cognitive unmanned aerial vehicle (UAV) network. Specifically, we first take into account the primary privacy information and the secondary maritime UAV’s quality of service. Then, we formulate an optimization problem [...] Read more.
This paper investigates the secure rate-splitting multiple access (RSMA) cooperation for the maritime cognitive unmanned aerial vehicle (UAV) network. Specifically, we first take into account the primary privacy information and the secondary maritime UAV’s quality of service. Then, we formulate an optimization problem to maximize UAV’s transmission rate according to the RSMA decoding principle and primary information security requirements. To solve this non-convex problem, we design a CPFS algorithm to allocate the transmit power and adjust the UAV’s location. In addition, the worst case is analyzed, which is the lower-bound secondary transmission rate. Finally, simulation results indicate that the proposed scheme improves the UAV’s transmission rate compared with the traditional schemes. Full article
(This article belongs to the Special Issue Air Base Station-Assisted Communications for Maritime Internet of Things)
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